A Generalized Software Reliability Growth Model Incorporating Testing-Coverage Operating in Random Field Environment with cost function

A Generalized Software Reliability Growth Model Incorporating Testing-Coverage Operating in Random Field Environment with cost function | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Generalized Software Reliability Growth Model Incorporating Testing-Coverage Operating in Random Field Environment with cost function Akshay Kumar Yadav, Millie Pant, Shilpa Srivastava This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5436323/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract A human cannot imagine surviving in the current technological era without software, as software manufacturers focus heavily on creating software that is free of bugs and maintains reliability and compatibility with human activities that depend on software-enabled equipment. One important thing to look into is how the software will function in a random field condition. In this chapter, we develop a generalized software reliability growth model with generalized fault coverage function, considering the effects of random field environment. Two data sets are used, and the computational outcomes of the suggested models and the existing models are compared using the Least Square Estimation (LSE) approach in MATLAB software to show which model performs better. For comparison, the three goodness-of-fit metrics, the root mean square error, R-square, and sum of square error are also employed. Generalized Software Reliability Growth Model (G-SRGM) Non-Homogeneous Poisson Process (NHPP) Generalized Testing Coverage Function (G-TCF) Random Operating Environment Least Square Estimation (LSE) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5436323","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":381801124,"identity":"2677b59d-302b-40c9-b64e-6f552967722c","order_by":0,"name":"Akshay Kumar Yadav","email":"","orcid":"","institution":"Indian Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Akshay","middleName":"Kumar","lastName":"Yadav","suffix":""},{"id":381801125,"identity":"bb18c1ae-e3aa-433b-8335-f7ce78d61b62","order_by":1,"name":"Millie Pant","email":"","orcid":"","institution":"Indian Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Millie","middleName":"","lastName":"Pant","suffix":""},{"id":381801126,"identity":"b6302dd9-ebe9-49dd-8109-513b3ba4a031","order_by":2,"name":"Shilpa Srivastava","email":"data:image/png;base64,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","orcid":"","institution":"Christ University","correspondingAuthor":true,"prefix":"","firstName":"Shilpa","middleName":"","lastName":"Srivastava","suffix":""}],"badges":[],"createdAt":"2024-11-12 05:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5436323/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5436323/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72722234,"identity":"63424641-b559-4423-9d71-303526bd725d","added_by":"auto","created_at":"2024-12-31 22:31:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":861841,"visible":true,"origin":"","legend":"","description":"","filename":"PaperAutomatedSE.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5436323/v1_covered_aa4f6498-ce5a-4dd8-837e-160b9d497be5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Generalized Software Reliability Growth Model Incorporating Testing-Coverage Operating in Random Field Environment with cost function","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Generalized Software Reliability Growth Model (G-SRGM), Non-Homogeneous Poisson Process (NHPP), Generalized Testing Coverage Function (G-TCF), Random Operating Environment, Least Square Estimation (LSE)","lastPublishedDoi":"10.21203/rs.3.rs-5436323/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5436323/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"A human cannot imagine surviving in the current technological era without software, as software manufacturers focus heavily on creating software that is free of bugs and maintains reliability and compatibility with human activities that depend on software-enabled equipment. 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